Panacea aims to build an intelligent recommendation system to effectively propose drug therapies that will support and facilitate health professionals, ensuring faster and safer administration of drugs. For this purpose, Panacea will make use of Semantic Web technologies for the formal representation of the involved knowledge and to provide automated inference.

PractiKPharma (Practice-based evidences for actioning Knowledge in Pharmacogenomics) aims at validating, or moderating, PGx state-of-the-art (SOTA) knowledge on the basis of practice-based evidences, i.e., knowledge extracted from EHRs. Units of knowledge in PGx typically have the form of ternary relationships gene variant–drug–adverse event, and can be formalized to different extents using biomedical ontologies. To reach this goal, the PractiKPharma consortium proposes to focus on four objectives: (1) to extract SOTA knowledge from PGx databases and literature, (2) to extract observational knowledge (i.e., knowledge extracted from observational data) from EHRs, (3) to compare knowledge units extracted from these two origins, to confirm or moderate SOTA knowledge, with the goal of enabling personalized medicine. (4) Finally, to emphasize newly confirmed knowledge, omics databases will be investigated for molecular mechanisms that underlie and explain drug adverse events. This investigation will use and contribute to the biomedical Linked Open Data.

The Retrospective Analytics System (RAS) is based on semantic and linguistic information technologies. It empowers German clinics and offices to analyse, interpret and automatically process the growing amount of free text in electronic medical documents. For instance, clinics can benefit from a deeper understanding of the imaging utilization of physicians as well as of potential quality issues in radiological reports.